Microsoft Proposes OAT for LLM Agent Failure Attribution

Microsoft and collaborators introduced OAT, a novel method for debugging LLM agent trajectories at scale. By learning exclusively from successful trajectories, OAT efficiently identifies the exact step that caused a task failure, avoiding the high computational costs of traditional prompt-based approaches.

2026-07-15 ~ 2026-07-16 · 2 related posts

• Microsoft's OAT: Debugging Agents Using Only Success Trajectories — omarsar0 · 2026-07-15
• OAT: Finding Failed Steps via Successful Trajectories — Samuel Yeh · 2026-07-16